Nordic economic growth in light of new theory : overoptimism about R&D and human capital?

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Abstract

The idea that education is important for economic growth has existed for a long time. Recently, that an educated population is vital for the economy to grow has been emphasized and a number of theories trying to explain the link between education and economic growth have emerged. In addition to education, economic theory points out R&D as the main engine of growth. However, it is not only economists that believe that education and R&D are important. Since World War II, the Nordic countries and the other OECD economies have devoted more and more resources to these activities.

Over the last 50 years, time spent accumulating skills through formal education has increased. The average level of schooling in the total population was in 1995 over 11 years in all Nordic countries. There are cross-country differences in the increase in educational attainment. For instance, average years of schooling has increased by almost four years in Finland from 1960 to 1995, while in Denmark over the same period, average years of schooling increased by only one year.

A second pattern in the Nordic countries and the other OECD economies since 1945 is that the search for new ideas has intensified. Both the number of people engaged in R&D activities and the R&D expenditure as a percentage of GDP have increased substantially. It is Sweden and Finland that currently devote most resources to R&D in the Nordic countries. In 1995, Sweden and Finland spent about three and two percent of their GDP on R&D. In the same year, the R&D expenditure as a percentage of GDP in Norway and Denmark was 1.7 and 1.9, respectively. 30 years earlier, all the countries devoted about one percent of their GDP on R&D activities.

The period since World War II has also been a period of large economic growth. Over this period of about 50 years, the average annual growth rate of per capita GDP in the Nordic countries have been around three percent. However, there are major cross-country differences. From 1945 to 1995, Norway experienced an average growth of per capita GDP of 3.4 percent per year, whereas over the same period of time, the average annual growth in Sweden was 2.3 percent. As a result of these growth rate differences, in 1995, the GDP per capita level in Norway was over four times the level in 1945, whereas the GDP per capita level in Sweden only doubled.

In this paper I will examine if it is possible to explain the growth in Nordic per capita GDP and the cross-country differences with R&D and human capital. A number of authors, e.g. Mankiw et al. (1992), Lichtenberg (1993), Andrés et al. (1996) and Barro (1997), have presented empirical investigation in the same spirit . However, their theoretical frameworks differ and they do not focus on the Nordic countries, but use samples consisting of a large number of countries. Data from the Nordic countries are, traditionally, of high quality and the Nordic countries are quite similar societies. Thus, in my sample, poor data and omitted variables will, hopefully, cause fewer problems than in the above mentioned empirical investigations and the analysis could thus perhaps help in answering the question if some of the Nordic countries would gain from adjusting their R&D and education policy.

Section 2 starts with a brief history of economic growth theory, emphasizing endogenous growth models. It also offers an explanation of why I have chosen a Schumpeterian growth model as a framework for my analysis. In section 2.2 a formal growth model, admittedly only one of many possible candidates, is presented and the key results are discussed. The model is suggested in Howitt (2000). However, the model used in the present study is extended to include accumulation of human capital. In addition to including traditional Solow-type determinants of GDP per capita, this model predicts a higher steady-state level of per capita GDP the higher the R&D expenditure as a percentage of GDP and the higher the level of the human capital stock are. Outside steady-state, controlling for variables such as the human and physical capital stock and the country's technological level, the model predicts a higher per capita GDP growth rate the higher the R&D expenditure as a percentage of GDP is. In section 2.3 the empirical specification is derived and some alternative specifications are suggested.

Section 3 discusses the data that I use. In particular, I focus on the measurement problems of human capital and R&D expenditure and I discuss the improvements in measuring the former that have taken place by de la Fuente and Doménech (2000).

Section 4 gives an overview of the development of GDP per capita, educational attainment and resources devoted to R&D in the Nordic countries since 1945. Focus is on cross-country differences. Section 4 also includes plots of GDP per capita growth rates against GDP per capita levels, finding a negative relationship in support of the convergence hypothesis.

The results of the empirical investigation are presented in section 5. It starts with a preliminary examination of the impact of education and R&D on growth; plotting GDP per capita growth rates against the level of the human capital stock and the level of the R&D expenditures. I find a significant negative relationship between both the level of human capital and growth and between R&D expenditures and growth. However, I conclude that one cannot draw definite conclusions from such an investigation, since there are substantial correlations between different determinants of growth. In section 5.2 the parameters of the model developed in section 2 are estimated. When using pooled data at five-year intervals, the empirical results and the model's predictions are consistent except with respect to the impact of R&D expenditure on growth. Even though the model explains a large part of the interspatial differences in economic growth, a stability analysis concerning the length of the intervals in the sample show that in particular the coefficient on human capital is unstable, throwing doubt on the model s predictions. The most robust coefficient is on the "initial level of GDP", always negative, giving support to the convergence hypothesis. The coefficient on R&D expenditure is stable, but negative, throwing even more doubt on the theoretical model's predictions.

Section 6 offers some concluding remarks, recognizing the problem of drawing strong conclusions, given the data quality and due to the small number of observations in my sample. However, the positive impact of R&D and education on economic growth that several papers take for granted , do not show up in data. Thus, in light of the empirical results, I ask the question if endogenous growth advocates have been too optimistic about the role human capital and R&D have in explaining growth.